Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
Paper • 2311.03099 • Published • 33
How to use jeiku/SmarterAdult_3B_GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="jeiku/SmarterAdult_3B_GGUF", filename="SmarterAdult-Q2_K.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
How to use jeiku/SmarterAdult_3B_GGUF with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf jeiku/SmarterAdult_3B_GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf jeiku/SmarterAdult_3B_GGUF:Q2_K
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf jeiku/SmarterAdult_3B_GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf jeiku/SmarterAdult_3B_GGUF:Q2_K
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf jeiku/SmarterAdult_3B_GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf jeiku/SmarterAdult_3B_GGUF:Q2_K
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf jeiku/SmarterAdult_3B_GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf jeiku/SmarterAdult_3B_GGUF:Q2_K
docker model run hf.co/jeiku/SmarterAdult_3B_GGUF:Q2_K
How to use jeiku/SmarterAdult_3B_GGUF with Ollama:
ollama run hf.co/jeiku/SmarterAdult_3B_GGUF:Q2_K
How to use jeiku/SmarterAdult_3B_GGUF with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for jeiku/SmarterAdult_3B_GGUF to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for jeiku/SmarterAdult_3B_GGUF to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jeiku/SmarterAdult_3B_GGUF to start chatting
How to use jeiku/SmarterAdult_3B_GGUF with Docker Model Runner:
docker model run hf.co/jeiku/SmarterAdult_3B_GGUF:Q2_K
How to use jeiku/SmarterAdult_3B_GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jeiku/SmarterAdult_3B_GGUF:Q2_K
lemonade run user.SmarterAdult_3B_GGUF-Q2_K
lemonade list
This is a merge of pre-trained language models created using mergekit.
This model was merged using the DARE TIES merge method using jeiku/Rosa_v1_3B as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: jeiku/Rosa_v1_3B+jeiku/Bluemoon_cleaned_StableLM
parameters:
weight: 0.120
density: 0.125
- model: jeiku/Rosa_v1_3B+jeiku/Humiliation_StableLM
parameters:
weight: 0.1
density: 0.125
- model: jeiku/Rosa_v1_3B+jeiku/No_Robots_Alpaca_StableLM
parameters:
weight: 0.2
density: 0.125
- model: jeiku/Rosa_v1_3B+jeiku/Gnosis_StableLM
parameters:
weight: 0.125
density: 0.125
- model: jeiku/Rosa_v1_3B+jeiku/Erotica_StableLM
parameters:
weight: 0.125
density: 0.125
- model: jeiku/Rosa_v1_3B+jeiku/smol_PIPPA_StableLM
parameters:
weight: 0.2
density: 0.125
- model: jeiku/Rosa_v1_3B+jeiku/Toxic_DPO_StableLM
parameters:
weight: 0.175
density: 0.125
merge_method: dare_ties
base_model: jeiku/Rosa_v1_3B
parameters:
dtype: bfloat16
2-bit
6-bit
16-bit